Students in the sciences, economics, psychology, social sciences, and medicine take introductory statistics. Statistics is increasingly offered at the high school level as well. However, statistics can be notoriously difficult to teach as it is seen by many students as difficult and boring, if not irrelevant to their subject of choice. To help dispel these misconceptions, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, examples and projects that involve active student participation. Part I of the book presents a large selection of activities for introductory statistics courses and combines chapters such as, 'First week of class', with exercises to break the ice and get students talking; then 'Descriptive statistics' , collecting and displaying data; then follows the traditional topics - linear regression, data collection, probability and inference. Part II gives tips on what does and what doesn't work in class: how to set up effective demonstrations and examples, how to encourage students to participate in class and work effectively in group projects. A sample course plan is provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics and sampling.

In modern American presidential campaigning, scholars and citizens have bemoaned the effects of electronic media on voters. Much has been written about the effects of television ads, media management, perceived bias, and other issues, yet one element of today’s media environment that most Americans would recognize has not been identified in the public mind: expectation setting. Journalists regularly tell audiences what actions candidates should take on the campaign trail, based solely on whether they’re leading or trailing in public opinion polls. Polls, Expectations, and Elections: TV News Making in U.S. Presidential Campaigns follows therise and proliferation of this phenomenon through a comprehensive content analysis of transcripts of CBS Evening News broadcasts during presidential election campaigns from 1968–2012. Richard Craig uses numerous examples from these transcripts to illustrate how television news has gone from simply reporting poll data to portraying it as nearly the only motivation for anything candidates do while campaigning. He argues that with the combination of heightened coverage of campaigns and the omnipresence of poll data, campaign coverage has largely become a day-to-day series of contests, with candidates portrayed as succeeding or failing each day to meet “expectations” of what the candidate at a given position in the polls should do on the campaign trail. Highlighting the change in news media and candidate coverage, Polls, Expectations, and Elections will appeal to scholars of media studies, political communication, and journalism.

In this book, prominent social scientists describe quantitative models in economics, history, sociology, political science, and psychology.

This update of a lively, first-of-its-kind study of polling misfires and fiascoes in U.S. presidential campaigns takes up pollsters’ failure over the decades to offer accurate assessments of the most important of American elections. Lost in a Gallup tells the story of polling flops and failures in presidential elections since 1936. Polls do go bad, as outcomes in 2020, 2016, 2012, 2004, and 2000 all remind us. This updated edition includes a new chapter and conclusion that address the 2020 polling surprise and considers whether polls will get it right in 2024. As author W. Joseph Campbell discusses, polling misfires in presidential elections are not all alike. Pollsters have anticipated tight elections when landslides have occurred. They have pointed to the wrong winner in closer elections. Misleading state polls have thrown off expected national outcomes. Polling failure also can lead to media error. Journalists covering presidential races invariably take their lead from polls. When polls go bad, media narratives can be off-target as well. Lost in a Gallup encourages readers to treat election polls with healthy skepticism, recognizing that they could be wrong.

The 2016 Presidential Election: The Causes and Consequences of a Political Earthquake critically analyzes the 2016 presidential election. The chapters in this book identify key factors behind the election of Donald J. Trump, explore the unconventional campaign, analyze the unexpected election result, evaluate the forecasting models, and speculate on the effect of the election outcome on politics and governance in the Trump Administration.

All political scientists aim to explain politics. In addition to this goal, Michael Lewis-Beck and Tom Rice aim to forecast political events, specifically election results. In "Forecasting Elections" the authors systematically develop easy-to-understand models based on national economic and political measures to forecast eleciton results for the U.S. presidency, House of Representatives, Senate, governorships, and state legislatures. For comparative purposes, the more complex French electoral system is studied. In the final chapter the authors instruct readers on how to use the models to make their own forecasts of future elections. -- From publisher's description.

"One of the more momentous books of the decade." —The New York Times Book Review Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger—all by the time he was thirty. He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of the website FiveThirtyEight. Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data. Most predictions fail, often at great cost to society, because most of us have a poor understanding of probability and uncertainty. Both experts and laypeople mistake more confident predictions for more accurate ones. But overconfidence is often the reason for failure. If our appreciation of uncertainty improves, our predictions can get better too. This is the “prediction paradox”: The more humility we have about our ability to make predictions, the more successful we can be in planning for the future. In keeping with his own aim to seek truth from data, Silver visits the most successful forecasters in a range of areas, from hurricanes to baseball to global pandemics, from the poker table to the stock market, from Capitol Hill to the NBA. He explains and evaluates how these forecasters think and what bonds they share. What lies behind their success? Are they good—or just lucky? What patterns have they unraveled? And are their forecasts really right? He explores unanticipated commonalities and exposes unexpected juxtapositions. And sometimes, it is not so much how good a prediction is in an absolute sense that matters but how good it is relative to the competition. In other cases, prediction is still a very rudimentary—and dangerous—science. Silver observes that the most accurate forecasters tend to have a superior command of probability, and they tend to be both humble and hardworking. They distinguish the predictable from the unpredictable, and they notice a thousand little details that lead them closer to the truth. Because of their appreciation of probability, they can distinguish the signal from the noise. With everything from the health of the global economy to our ability to fight terrorism dependent on the quality of our predictions, Nate Silver’s insights are an essential read.